No student was selected because of current or past alcohol problems, and based on questions extracted from the Semi-Structured Assessment for the Genetics of Alcoholism interview , the protocol excluded nondrinkers, individuals with severe psychiatric diagnoses , students who ever met DSM-IV criteria for dependence on alcohol or illicit drugs , and Asian individuals who became physically ill after one standard drink . Five-hundred subjects were enrolled, half above and half below the median for the number of drinks required for effects the first five times of drinking using the Self Report of the Effects of Alcohol questionnaire. The SRE determines the mean number of standard drinks needed across up to four possible alcohol effects actually experienced early in the drinking career. These included the drinks required to produce any effect, slurred speech, unsteady gait, and unwanted falling asleep. The SRE has Cronbach alphas and repeat reliabilities >.88 . This retrospective self-report measure was used rather than alcohol challenges because the latter are too expensive and time consuming for use in a large population . The overlap between SRE and alcohol challenge-based LRs in predicting heavy drinking and alcohol problems is 60%, and the measures produce similar results when used in different generations of the same families . High and low LR subjects were randomly assigned to three conditions: those who watched 5 videos regarding two different prevention approaches and no-intervention controls. The latter helped control for general-campus-related changes in drinking over time, and, reflecting the emphasis in the larger study on the impact of education groups,pot drying most students were assigned to active education.Analyses began with data transformations based on distributional properties for numbers of ARBs and maximum drinks per occasion using inverse reflected and square root transformations, respectively.

For the first set of analyses, to address Hypotheses 1–3, numbers of ARBs per assessment were compared across ethnic groups overall, ethnic groups among females and males separately, and ethnic groups among subjects with high and low LRs separately. As shown in Table 3 regarding each figure, at each assessment ethnic group differences were evaluated using two one-way ANOVAs, first presenting the F-value for differences in prior month ARBs across ethnic groups without controlling covariates, and again as F values controlling for maximum drinks consumed the prior month and for education group assignment . The final analysis in Table 4 addressed Hypothesis 4 by evaluating main and interaction effects for numbers of ARBs across eight time points using a 3 ethnic groups by 2 sexes by 2 LR categories by 8 time points mixed-design ANOVA that controlled for maximum drinks while using education group as a covariate. For all analyses, missing data were handled through a maximum likelihood procedure . At baseline, the 398 eligible participants were 18-year-old UCSD freshmen, of whom 62% were female with 40% EA, 20% Hispanic, and 41% of Asian descent . Table 2 presents the numbers of subjects across combinations of ethnicities, sex, and LR groups. The SRE values averaged 4 drinks across four possible effects actually experienced the first five times they drank. In the prior month, these students consumed on average 6 maximum and 4 usual drinks per occasion, with 4 drinking occasions per month. At baseline, 21% noted having experienced an ARB in the prior month, with an average of 0.33 such episodes . About 40% had used cannabis the prior month, and 87% were in the active intervention group in the prevention study. Table 3 presents statistical analyses associated with the 3 figures, while Table 4 shows results of a mixed-design ANOVA for the overall statistical analysis regarding Hypothesis 4. These statistical results are mentioned here because they relate to interpretations of Hypotheses. Figure 1 presents the average number of ARBs the month before each assessment for members of the three ethnic groups, with highest rates for EA students, lowest for Asian individuals, and an intermediate rate for Hispanic students. While not shown in the figures, over the 55 weeks 43.0% had at least 1 ARB, including 13.3% with 1, 8.8% with 2, 2.5% each with 4, 5, or 6 ARBs, and 0 to 1.0% each with between 7 and a maximum of 36 ARBs.

As demonstrated by the absence of a significant ethnicity by time interaction in Table 4, general patterns of ups and downs in numbers of ARBs over 55-weeks were similar for the three groups where ARB values tended to diminish between January and March , increase in June in concert with a campus festival known for heavy drinking, decrease again over the summer when most students returned home , and rose after returning to school . However, regarding Figure 1, as shown in Table 3 the ANOVAs carried out at each time point revealed significant differences in the average number of ARBs across groups at every evaluation. After controlling for maximum drinks reported at each assessment and education group assignment, residual statistics for ethnic group differences in ARBs at each time point across EA, Hispanic, and Asian subjects remained significant at Times 2 and 4. The absence of a main effect for ethnicity in the mixed-design ANOVA in Table 4 indicates the possibility that other characteristics may have impacted results. Therefore, Figure 2 presents ARB trajectories for the three ethnic groups for female and male students separately. While not shown, during the 55 weeks, 48.0% of females and 34.7% of males reported at least one ARB, with an average of 0.30 and 0.19 ARBs per assessment, respectively. Ethnic group differences in ARBs were prominent among females, with the highest ARB rates for EA women, the lowest for Asian individuals, and intermediate, but relatively low, rates for Hispanics. Looking at each assessment for females, statistical analyses in Table 3 demonstrate significant ethnic differences in the rates of ARBs for raw ARB numbers at every assessment, which remained significant at times 4, 5 and 8 after controlling for education group and maximum drinks. Differences across ethnic groups were less apparent for males, and the ethnicity by sex by time interaction was significant in Table 4. Also, for between subjects’ analyses where time was collapsed and average scores across the eight time points were used, there was a significant sex main effect, and the ethnicity by sex interaction was a trend . Next, the potential relationship of LR to the ethnic patterns of ARBs over time was evaluated in Figure 3. Here, high and low LR subjects showed the same general pattern of ARBs across time demonstrated in Figure 1,cannabis drying including highest rates of ARBs per assessment for EA, lowest for Asian, and intermediate rates for Hispanic students. However, ethnic group differences in ARBs were more robust for high LR subjects, with Table 3 revealing significant differences in raw ARB numbers across the three ethnic groups at every assessment, which remained significant at Time 7 after controlling for maximum drinks and education group assignment, with a trend at Time 4 .

The only significant differences in raw ARB numbers for low LR subjects were noted at Time 2 and 4, each of which lost significance once residuals were used. In Table 4 the sex by LR by time interaction was significant and the LR group by time interaction for patterns of ARBs was a trend . Thus, the relationship of LR to differences in ARB patterns across ethnic groups was modest, and was most robust when considered in the context of sex effects. Regarding Hypothesis 4, as briefly alluded to above, the overall analysis in Table 4 indicates interactions regarding ARBs among ethnicity, sex, and LR in two 3-way interactions . However, the 4-way interaction was not significant. It is important to note that cross-sectional data in Figures 1 to 3 were analyzed after controlling for the education group in which students participated. Table 4 offers additional information about effects of educational group assignment, which was used as a covariate. Here, the education group by time interaction was a trend , and the education group main effect was significant, with controls having higher ARB frequencies than the active education participants.Alcohol-related blackouts are highly prevalent phenomena associated with potentially severe problems . Recently, the prevalence of ARBs has reached alarming rates, especially in females and individuals with early onset drinking . The UCSD freshmen studied here are no exception to these trends as 43% of these students reported at least 1 ARB during the 55 weeks, including 48% in females and 35% in males. While the risk for these alcohol-related anterograde memory lapses increases with BACs , ARB vulnerabilities were also related to ethnic background, female sex, and levels of response to alcohol. The patterns and interactions among these characteristics are the focus of this paper. The current analyses added potentially useful data to the study of ARBs. The sample is relatively large, and subjects were assessed prospectively eight times over 55 weeks during a life-period likely to involve heavy drinking . Several assessments were scheduled at periods when the rates of ARBs were likely to change, including following a heavy drinking campus festival, summer break, and after returning to school as sophomores.

Data were evaluated while controlling for maximum drinks, thus diminishing the possibility that ARB patterns simply reflected impacts of heavy drinking itself, and after controlling for possible effects of the prevention trial from which the data were extracted. The major questions focused on improving understanding of how ethnicity, sex, and LR related to rates of ARBs. To address Hypothesis 1, evaluations began with documentation of expected ethnic group differences in rates of ARBs across time. Consistent with most prior studies, the highest rates were observed for students of EA origin, the lowest among Asian students, with an intermediate rate for Hispanic individuals. This pattern of the number of ARBs persisted after controlling for maximum drinks and the prevention group in which a person participated in the larger study. While fluctuations in ARBs across the year were fairly similar for the three ethnic groups , rates of ARBs were different across ethnicities. As suggested by several recent papers and predicted in the first part of Hypothesis 2, women had higher ARB rates. However, contrary to the second half of that hypothesis, the relationship of ethnicities to ARBs over time was different in females and males. The expected pattern of highest ARBs in EA students and lowest in Asian individuals was most obvious for females and less prominent for males. The mixed-design ANOVA in Table 4 demonstrated significant sex main effects, as well as ethnicity by sex by time and sex by LR by time interactions. The key role of sex in the rates of ARBs over 55 weeks and the interactions of sex with ethnicity might reflect several mechanisms. First, women develop higher BACs per drink , which may translate into higher risks for ARBs. The differences across ethnicities may be especially strong in women vs. men as Asian and Hispanic women may also have stronger culture-based prohibitions against heavier drinking than seen in EA cultures . Also, while more research is needed, considering recent documentation of potentially genetically-related physiologic characteristics that may relate to the BAC required for ARBs , higher rates of ARBs in EA women might reflect some sex-related biological mechanisms that contribute directly to the ARB risk. The first part of Hypothesis 3 was also supported in that a low LR was related to higher ARB rates in these subjects. However, the data in Figure 3 indicate that the relationships of ethnicity to ARBs differ in high- and low-LR subjects. It is possible that greater differential in ethnicity-related ARB risks might be observed primarily in subjects with higher LRs where drinking quantities are not already elevated by a low sensitivity to alcohol.Finally regarding hypotheses, the prediction that the ethnic group status will interact with sex and LR to predict ARB propensity was partially supported. Table 4 demonstrates significant 3-way interactions for ethnicity by sex by time and sex by LR by time, but the overall 4-way interaction was not significant . Still, the findings underscore the contention that there is more to ARBs than just how much a person drinks, and support the prediction that ethnicity, sex and LR all relate to ARB patterns.